Puppet-master, simple and scalable (programmatic) website interaction

Hacker News

Did you ever need to interact with a website, not only using plain http but a real browser? Have you ever felt the pain using selenium or struggled reading data from a rendered SPA website? We did, and we suffered. During development of a SaaS platform we built puppet-master, a scalable and flexible way of interacting with websites using well known and plain EcmaScript 6, wrapped in a simple API and thus usable by most programming languages. You can find the docs at https://docs.puppet-master.io/ and any feedback is greatly appreciated!

Visit product View on Hacker NewsSep 19, 2018

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Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

77%77% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: using, plain · Missing: mac, agents, macos

75%75% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

67%67% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoStrong fit for a featured deal · Strong signals: platform · Missing: plus, intuitive, reviews

60%60% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

11%11% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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